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COLT
2004
Springer
16 years 10 days ago
Learning Classes of Probabilistic Automata
Abstract. Probabilistic finite automata (PFA) model stochastic languages, i.e. probability distributions over strings. Inferring PFA from stochastic data is an open field of rese...
François Denis, Yann Esposito
ROCAI
2004
Springer
16 years 9 days ago
Learning Interestingness Measures in Terminology Extraction. A ROC-based approach
Abstract. In the field of Text Mining, a key phase in data preparation is concerned with the extraction of terms, i.e. collocation of words attached to specific concepts (e.g. Ph...
Mathieu Roche, Jérôme Azé, Yve...
FLAIRS
2008
15 years 9 months ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar
DAGSTUHL
2007
15 years 8 months ago
Learning Probabilistic Relational Dynamics for Multiple Tasks
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...
ACL
2006
15 years 8 months ago
Semi-Supervised Learning of Partial Cognates Using Bilingual Bootstrapping
Partial cognates are pairs of words in two languages that have the same meaning in some, but not all contexts. Detecting the actual meaning of a partial cognate in context can be ...
Oana Frunza, Diana Zaiu Inkpen